How can a chatbot help you in your prospecting?

Here is why and how to create a prospecting chatbot on your website.

Introduction

Installing a chatbot on Facebook Workplace is quite simple. Just create a new custom integration, fill in a few fields in a savvy fashion, and copy/paste the app ID and app secret into Vizir.

Let’s go to see the details of all this.

A chatbot for prospecting, what is it for?

The user experience has changed.

From now on, it is often no longer the salesperson who guides the prospect in an initiatory process leading to the purchase. It is the user who decides what content to pick to form an opinion on the brand or service offered.

Thanks to well-crafted inbound strategies, potential customers are exposed to information about the brand universe at every stage of their journey.

With a few clicks, they can find reviews of your services, see the rates and decide if you can meet their needs.

Some Internet users will want to get in touch with your teams, and beware because here, impatience is a curse… The more time passes, the less Internet users seem to be ready to devote themselves to research:

Leads are 10 times less likely to respond after a 5-minute wait
A company that responds to its leads in less than an hour is 7 times more likely to qualify them than companies that respond in 2 hours or more.

We need to be able to respond quickly. But that’s not all, these answers must also match the needs of your prospect.

Thanks to this article, learn all the methods that will transform your commercial prospection routines into foolproof war machines to generate business.

What are the objectives of a prospecting chatbot?

A chatbot is a conversational tool that will take over during your absence. It takes care of the first contacts with your potential customers.

In addition to breaking the ice, it gathers information that will allow you to enrich your leads.

Its main objectives are:

Pre-qualify your leads: the more precise questions you ask about your prospect’s user behavior, the more you can estimate their warmth level and score them.
Collect concrete data: by engaging your lead, you can collect a lot of information that will allow the marketing department to enrich the conversion tunnel and the sales department to adapt their sales pitch for a tailored approach.
Answer in real time: as mentioned above, it is better to provide direct answers to arouse the interest of a potential customer and ensure his retention. The less time you take to answer their questions, the more likely they are to convert.
Improve your response rate: when a robot is in charge of answering your leads efficiently while you are sleeping, it is a great asset.

As you can see, a prospecting chatbot can quickly take your business to another dimension.

Let’s see how the tool works.

How does a prospecting chatbot work?

To summarize a chatbot, let’s just say that it is an artificial intelligence program designed to understand and respond to text or voice commands.

Basically, a chatbot was just coded based on very simple dialogue scenarios.

In order for the response to be appropriate, the request had to correspond precisely to what the chatbot’s creator had taught it. Soon, the mechanism ran out of steam and the conversations reached a dead end.

To ensure that the experience of a chatbot is not disappointing, it is necessary to set it up properly.

Fortunately, the technique has developed quickly and most chatbots now work thanks to machine learning.

For example, at Vizir, we use a Natural Language Understanding brick, incorporated in our no-code bot creation interface.

There are several modes of operation:

The decision tree: this is clearly the simplest chatbot to set up. On the other hand, this requires the sales or marketing department to properly map out the user journey beforehand. It is the chatbot that starts the conversation by asking a question. For each question asked, the user can choose a pre-recorded answer. It then leads to a next question, until proposing to the prospect a Call-to-Action (appointment setting, dedicated resource, sale…)
Keyword recognition: this is the same system as the decision tree, the only difference being that the system is based on lexical recognition. The chatbot is therefore a bit freer and can interact according to the keywords proposed by the user. There is no pre-established scenario.
Deep learning: commonly called machine learning, deep learning is a little more precise. In concrete terms, it is a matter of machines learning to react to interactions and to think in an intelligent way, based on the structure of the human brain. While it’s the most engaging and fun chatbot for a prospect to use, it’s also the most expensive and the most expensive to set up. These include Alexa, Siri or Google Home.

Now you know how it works. Now, what are its features?

How does a prospecting chatbot work?

To summarize a chatbot, let’s just say that it is an artificial intelligence program designed to understand and respond to text or voice commands.

Basically, a chatbot was just coded based on very simple dialogue scenarios.

To ensure that the experience of a chatbot is not disappointing, it is necessary to set it up properly.

Fortunately, the technique has developed quickly and most chatbots now work thanks to machine learning.

For example, at Vizir, we use a Natural Language Understanding brick, incorporated in our no-code bot creation interface.

There are several modes of operation:

The decision tree: this is clearly the simplest chatbot to set up. On the other hand, this requires the sales or marketing department to properly map out the user journey beforehand. It is the chatbot that starts the conversation by asking a question. For each question asked, the user can choose a pre-recorded answer. It then leads to a next question, until proposing to the prospect a Call-to-Action (appointment setting, dedicated resource, sale…)
Keyword recognition: this is the same system as the decision tree, the only difference being that the system is based on lexical recognition. The chatbot is therefore a bit freer and can interact according to the keywords proposed by the user. There is no pre-established scenario.
Deep learning: commonly called machine learning, deep learning is a little more precise. In concrete terms, it is a matter of machines learning to react to interactions and to think in an intelligent way, based on the structure of the human brain. While it’s the most engaging and fun chatbot for a prospect to use, it’s also the most expensive and the most expensive to set up. These include Alexa, Siri or Google Home.

Now you know how it works. Now, what are its features?

What are the best chatbots for prospecting?

In the age of growth marketing, there are many solutions to automate your prospecting routine.

You can also find a selection of the best solutions in this article.

As far as pure conversational solutions are concerned, here is a selection of 5 tools:

Platform

Features

FAQ Bot

Ops Bot

Push Bot

Messaging platforms

Microsoft Teams

Microsoft Sharepoint

Cisco Webex

Widget web

By industry

Insurance

Retail

Industry

Public sector

By teams

IT bot

HR bot

Product bot

Learning

Blog

Tutorials

Replays

Docs

tools

ROI

Roadmap chatbot

Excel 2 bot

Partenaires

Microsoft

Cisco Webex

GLPI

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